dacapo.blockwise.watershed_function
===================================

.. py:module:: dacapo.blockwise.watershed_function


Functions
---------

.. autoapisummary::

   dacapo.blockwise.watershed_function.segment_function


Module Contents
---------------

.. py:function:: segment_function(input_array, block, offsets, bias)

   Segment the input array using the multicut watershed algorithm.

   :param input_array: The input array.
   :type input_array: np.ndarray
   :param block: The block to be processed.
   :type block: daisy.Block
   :param offsets: The offsets.
   :type offsets: List[Tuple[int]]
   :param bias: The bias.
   :type bias: float

   :returns: The segmented array.
   :rtype: np.ndarray

   .. rubric:: Examples

   >>> input_array = np.random.rand(128, 128, 128)
   >>> total_roi = daisy.Roi((0, 0, 0), (128, 128, 128))
   >>> read_roi = daisy.Roi((0, 0, 0), (64, 64, 64))
   >>> write_roi = daisy.Roi((0, 0, 0), (32, 32, 32))
   >>> block_id = 0
   >>> task_id = "task_id"
   >>> block = daisy.Block(total_roi, read_roi, write_roi, block_id, task_id)
   >>> offsets = [(0, 1, 0), (1, 0, 0), (0, 0, 1)]
   >>> bias = 0.1
   >>> segmentation = segment_function(input_array, block, offsets, bias)

   .. note:: DGA: had to add in flatten and reshape since remap (in particular indices) didn't seem to work with ndarrays for the input